Italo Zoppis

Italo Zoppis
Università degli Studi di Milano-Bicocca | UNIMIB · Department of Informatics, Systems and Communication (DISCo)

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91
Publications
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673
Citations
Citations since 2017
40 Research Items
465 Citations
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2017201820192020202120222023020406080
2017201820192020202120222023020406080
2017201820192020202120222023020406080

Publications

Publications (91)
Chapter
Temporal networks have been successfully applied to represent the dynamics of protein-protein interactions. In this paper we focus on the identification of dense subgraphs in temporal protein-protein interaction networks, a relevant problem to find group of proteins related to a given functionality. We consider a drawback of an existing approach fo...
Chapter
Learning and training processes are starting to be affected by the diffusion of Artificial Intelligence (AI) techniques and methods. AI can be variously exploited for supporting education, though especially deep learning (DL) models are normally suffering from some degree of opacity and lack of interpretability. Explainable AI (XAI) is aimed at cre...
Article
The problem of matching a query string to a directed graph, whose vertices are labeled by strings, has application in different fields, from data mining to computational biology. Several variants of the problem have been considered, depending on the fact that the match is exact or approximate and, in the approximate case, which edit operations are...
Preprint
As the worldwide population gets increasingly aged, in-home telemedicine and mobile-health solutions represent promising services to promote active and independent aging and to contribute to a paradigm shift towards patient-centric healthcare. In this work, we present ACTA (Advanced Cognitive Training for Aging), a prototype mobile-health solution...
Article
Full-text available
A central problem in graph mining is finding dense subgraphs, with several applications in different fields, a notable example being identifying communities. While a lot of effort has been put in the problem of finding a single dense subgraph, only recently the focus has been shifted to the problem of finding a set of densest subgraphs. An approach...
Preprint
Full-text available
Objective: To evaluate the impact on Electroencephalography (EEG) classification of different kinds of attention mechanisms in Deep Learning (DL) models. Methods: We compared three attention-enhanced DL models, the brand-new InstaGATs, an LSTM with attention and a CNN with attention. We used these models to classify normal and abnormal (i.e., artif...
Article
Full-text available
Conscious and functional use of online social spaces can support the elderly with mind cognitive impairment (MCI) in their daily routine, not only for systematic monitoring, but to achieve effective targeted engagement. In this sense, although social involvement can be obtained when elder’s experiences, interests, and goals are shared and accepted...
Chapter
The problem of matching a query string to a directed graph, whose vertices are labeled by strings, has application in different fields, from data mining to computational biology. Several variants of the problem have been considered, depending on the fact that the match is exact or approximate and, in this latter case, which edit operations are cons...
Preprint
The problem of matching a query string to a directed graph, whose vertices are labeled by strings, has application in different fields, from data mining to computational biology. Several variants of the problem have been considered, depending on the fact that the match is exact or approximate and, in this latter case, which edit operations are cons...
Conference Paper
Full-text available
Emerging studies in the deep learning community focus on techniques aimed to identify which part of a graph can be suitable for making better decisions and best contributes to an accurate inference. These researches (i.e., “attentional mechanisms” for graphs) can be applied effectively in all those situations in which it is not trivial to capture d...
Conference Paper
Full-text available
Recent studies in the context of machine learning have shown the effectiveness of deep attentional mechanisms for identifying important communities and relationships within a given input network. These studies can be effectively applied in those contexts where capturing specific dependencies, while downloading useless content, is essential to take...
Chapter
Mind Cognitive Impairment is one of the most common clinical manifestations affecting the elderly. In this paper, we report the work in progress (in the frame of our SENIOR project) to provide elderly with new Nudge theory driven advices for influencing their interest to a conscious and functional participation to “targeted” social communities wher...
Article
Inspired by scaffold filling, a recent approach for genome reconstruction from incomplete data, we consider a variant of the well-known longest common subsequence problem for the comparison of two sequences. The new problem, called Longest Filled Common Subsequence, aims to compare a complete sequence with an incomplete one, i.e. with some missing...
Article
Full-text available
Patients who survive brain injuries may develop Disorders of Consciousness (DOC) such as Coma, Vegetative State (VS) or Minimally Conscious State (MCS). Unfortunately, the rate of misdiagnosis between VS and MCS due to clinical judgment is high. Therefore, diagnostic decision support systems aiming to correct any differentiation between VS and MCS...
Chapter
Objective: Mild Cognitive Impairment (MCI) is rapidly becoming one of the most common clinical manifestation affecting the elderly. The main aim of the SENIOR Project [SystEm of Nudge theory-based Information and Communications Technology (ICT) applications for OldeR citizens] is the development and validation of a new Nudge theory-based ICT coach...
Chapter
The identification of cohesive communities (dense subgraphs) is a typical task applied to the analysis of social and biological networks. Different definitions of communities have been adopted for particular occurrences. One of these, the 2-club (dense subgraphs with diameter value at most of length 2) has been revealed of interest for applications...
Article
We study a variant of the problem of finding a collection of disjoint s-clubs in a given network. Given a graph, the problem asks whether there exists a collection of at most r disjoint s-clubs that covers at least k vertices of the network. An s-club is a connected graph that has diameter bounded by s, for a positive integer s. We demand that each...
Preprint
Full-text available
A central problem in graph mining is finding dense subgraphs, with several applications in different fields, a notable example being identifying communities. While a lot of effort has been put on the problem of finding a single dense subgraph, only recently the focus has been shifted to the problem of finding a set of dens- est subgraphs. Some appr...
Chapter
Finding cohesive subgraphs in a network is a well-known problem in graph theory. Several alternative formulations of cohesive subgraph have been proposed, a notable example being s-club, which is a subgraph where each vertex is at distance at most s to the others. Here we consider the problem of covering a given graph with the minimum number of s-c...
Preprint
Finding cohesive subgraphs in a network is a well-known problem in graph theory. Several alternative formulations of cohesive subgraph have been proposed, a notable example being $s$-club, which is a subgraph where each vertex is at distance at most $s$ to the others. Here we consider the problem of covering a given graph with the minimum number of...
Article
Full-text available
We consider how the orthology/paralogy information can be corrected in order to represent a gene tree, a problem that has recently gained interest in phylogenomics. Interestingly, the problem is related to the Minimum CoGraph Editing problem on the relation graph that represents orthology/paralogy information, where we want to minimize the number o...
Article
Full-text available
We present the 10th Workshop on Biomedical and Bioinformatics Challenges for Computer Science – BBC2017, held in Zurich, 12 - 14 June 2017.
Article
Full-text available
The reductionist approach of dissecting biological systems into their constituents has been successful in the first stage of the molecular biology to elucidate the chemical basis of several biological processes. This knowledge helped biologists to understand the complexity of the biological systems evidencing that most biological functions do not a...
Conference Paper
Obesity is now one of the most critical and demanding public health condition due to the correlation with many medical and psychological comorbidities, such as cardiovascular, orthopedic, pneumological, endocrinological, psychopathological complications, above all the type 2 diabetes. Obesity traditionally needs long and expensive treatments in a c...
Article
The current study proposes the successful use of a mass spectrometry-imaging technology that explores the composition of biomolecules and their spatial distribution directly on-tissue to differentially classify benign and malignant cases, as well as different histotypes. To identify new specific markers, we investigated with this technology a wide...
Article
Introduction: Despite the unquestionable advantages of Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging in visualizing the spatial distribution and the relative abundance of biomolecules directly on-tissue, the yielded data is complex and high dimensional. Therefore, analysis and interpretation of this huge amount of informati...
Article
Full-text available
Biomarkers able to characterise and predict multifactorial diseases are still one of the most important targets for all the “omics” investigations. In this context, Matrix-Assisted Laser Desorption/Ionisation-Mass Spectrometry Imaging (MALDI-MSI) has gained considerable attention in recent years, but it also led to a huge amount of complex data to...
Chapter
We present a graph-based approach to support case vs control discrimination problems. The goal is to partition a given input graph in two sets, a clique and an independent set, such that there is no edge connecting a vertex of the clique with a vertex of the independent set. Following a parsimonious principle, we consider the problem that aims to m...
Article
Full-text available
A central issue in biological data analysis is that uncertainty, resulting from different factors of variability, may change the effect of the events being investigated. Therefore, robustness is a fundamental step to be considered. Robustness refers to the ability of a process to cope well with uncertainties, but the different ways to model both th...
Article
Full-text available
Several promising biomarkers have been found for RCC, but none of them has been used in clinical practice for predicting tumour progression. The most widely used features for predicting tumour aggressiveness still remain the cancer stage, size and grade. Therefore, the aim of our study is to investigate the urinary peptidome to search and identify...
Article
Full-text available
Social media, online social networks and apps for smartphones and tablets are changing the way we communicate. According to a recent Pew Research Center survey, 73% of Internet users among US adults engage in social networking to access, create, and share contents (Duggan and Smith, 2013). The number of smartphone users is growing worldwide [56% of...
Article
Full-text available
Chronic diseases and conditions typically require long-term monitoring and treatment protocols both in traditional settings and in out-patient frameworks. The economic burden of chronic conditions is a key challenge and new and mobile technologies could offer good solutions. mHealth could be considered an evolution of eHealth and could be defined a...
Article
Full-text available
Renal Cell Carcinoma (RCC) is typically asymptomatic and surgery usually increases patient's lifespan only for early stage tumours. Moreover, solid renal masses cannot be confidently differentiated from RCC. Therefore, markers to distinguish malignant kidney tumours and for their detection are needed. Two different peptide signatures were obtained...
Article
Full-text available
Defining the aggressiveness and growth rate of a malignant cell population is a key step in the clinical approach to treating tumor disease. The correct grading of breast cancer (BC) is a fundamental part in determining the appropriate treatment. Biological variables can make it difficult to elucidate the mechanisms underlying BC development. To id...
Article
In several areas, for example in bioinformatics and in AI planning, the Shortest Common Superstring problem (SCS) and variants thereof have been successfully applied for string comparison. In this paper we consider two variants of SCS recently introduced, namely Restricted Common Superstring (RCS) and Swapped Common Superstring (SRCS). In RCS we ar...
Article
Full-text available
Copy number alterations (CNAs) represent an important component ofgenetic variations. Such alterations are related with certain type ofcancer including those of the pancreas, colon, and breast, amongothers. CNAs have been used as biomarkers for cancer prognosis inmultiple studies, but few works report on the relation of CNAs withthe disease progres...
Conference Paper
Full-text available
Tamoxifen is currently used for the treatment of breast cancer. Response to tamoxifen in metastatic conditions is a primary issue in cancer development. We used a cohort of breast cancer patients, treated or not with tamoxifen, and combined these data with the gene signature of metastatic samples in order to investigate the genetic mechanism of met...
Article
Publishing personal data without giving up privacy is becoming an increasingly important problem in different fields. In the last years, different interesting approaches have been proposed, i.e. k-Anonymity and l-Diversity. Given an input table, these approaches partition its rows so that the computed partition satisfies some constraint, in order t...
Conference Paper
Full-text available
Specific genome copy number alterations, such as deletions and amplifications are an important factor in tumor development and progression, and are also associated with changes in gene expression. By combining analyses of gene expression and genome copy number we identified genes as candidate biomarkers of BC which were validated as prognostic fact...
Conference Paper
Full-text available
Copy–number alterations (CNAs) represent an important component of genetic variations and play a significant role in many human diseases. Such alterations are related to certain types of cancers, including those of the pancreas, colon, and breast, among others. CNAs have been used as biomarkers for cancer prognosis in multiple studies, but few work...
Article
Full-text available
Background Mass spectrometry is an important analytical tool for clinical proteomics. Primarily employed for biomarker discovery, it is increasingly used for developing methods which may help to provide unambiguous diagnosis of biological samples. In this context, we investigated the classification of phenotypes by applying support vector machine (...
Data
Full-text available
Supplementary Information (PDF file format).
Data
Supplementary Figure S2 (PNG file format) — Venn diagram. Venn diagram of differentially expressed proteins identified in collection 1 (A) and collection 2 (B). Evaluation of quantitative level was performed by applying DAve and DCI formulas, G-test and Student’s t-test. In brackets is reported the number of proteins matching with the features sele...
Data
Supplementary Table S1 (PNG file format) — Matrix of high-dimensional proteomic data obtained analyzing sample by means of the MudPIT approach. Rows represent features (e.g., m/z values, peptides or proteins), while columns indicate samples. In each cell it is reported a value corresponding to the parameter associated with feature. In particular, p...
Data
Supplementary Figure S4 (PNG file format) — Principal Component Analysis of peptide, protein and m/z, data of collection 1 and 2. Overview of protein, peptide and mass spectra data matrices performed by Principal Component Analysis (PCA) (15). PCA was applied by RapidMiner software. High-dimensionality of each data matrix was preliminarily reduced...
Data
Supplementary Figure S1 (PNG file format) — Sample collections and related experimental data selected and used for the study purpose. For each sample five different datasets were used. In addition to the global protein and peptide profiles, m/z precursor ions, specifically detected from the chromatographic steps corresponding to 60, 120 and 400 mM...
Data
Supplementary Figure S3 (PNG file format) — Rapid Miner workflow. Rapid Miner WF for the Feature selection (a) and model construction/validation (b) phases. Blocks correspond to simple processes in the whole design: each operator receives an input and delivers an output to the forward operator. The function of each block is shortly reported as foll...
Conference Paper
Full-text available
Background / Purpose: We focus on the role of copy number alteration (CNA) in assessing prognosis of patients with colorectal cancer (CRC) when a particular relational representation of patients is given. Main conclusion: We showed that even a prediction analysis, concerning the progression of CRC, as characterized by the given staging classif...
Conference Paper
In several areas, in particular in bioinformatics and in AI planning, Shortest Common Superstring problem (SCS) and variants thereof have been successfully applied. In this paper we consider two variants of SCS recently introduced (Restricted Common Superstring, \(\ensuremath{\text{\textsc{RCS}}}\)) and (Swapped Common Superstring, \(\ensuremath{\t...
Conference Paper
Mass Spectrometry (MS)-based technologies represent a promising area of research in clinical analysis. They are primarily concerned with measuring the relative intensity (i.e., signals) of many protein/peptide molecules associated with their mass-to-charge ratios. These measurements provide a huge amount of information which requires adequate tools...
Conference Paper
Mass Spectrometry (MS)-based technologies represent a promising area of research in clinical analysis. They are primarily concerned with measuring the relative intensity (abundance) of many protein/peptide molecules associated with their mass-to-charge ratios over a particular range of molecular masses. These measurements (generally referred as pro...
Conference Paper
Full-text available
The problem of publishing personal data without giving up privacy is becoming increasingly important. Different interesting formalizations have been recently proposed in this context, i.e. k-anonymity [17,18] and l-diversity [12]. These approaches require that the rows in a table are clustered in sets satisfying some constraint, in order to prevent...
Article
"Signal" alignments play critical roles in many clinical setting. This is the case of mass spectrometry data, an important component of many types of proteomic analysis. A central problem occurs when one needs to integrate (mass spectrometry) data produced by different sources, e.g., different equipment and/or laboratories. In these cases some form...
Article
Among the several “omics” techniques (Kolker, 2009), proteomics represents a promising area to define new biomarkers inbiological fluids which can characterize and predict multi-factorial diseases. Therefore, it is important also in this context to support the search with robust analysis which offers suitable models for available data. In this rega...
Article
The application of various clustering techniques for large-scale gene-expression measurement experiments is a well-established method in bioinformatics. Clustering is also usually accompanied by functional characterization of gene sets by assessing statistical enrichments of structured vocabularies, such as the gene ontology (GO) [Gene Ontology Con...
Article
Full-text available
We deal with a special class of games against nature which correspond to subsymbolic learning problems where we know a local descent direction in the error landscape but not the amount gained at each step of the learning procedure. Namely, Alice and Bob play a game where the probability of victory grows monotonically by unknown amounts with the res...
Article
To investigate the possibility of using the ClinProt technique to find serum cancer related diagnostic markers that are able to better discriminate healthy subjects from patients affected by renal cell carcinoma (ccRCC). Renal cell carcinoma is the most common malignancy of the kidney. Biomarkers for early detection, prognosis, follow-up, and diffe...
Article
Type 1 diabetes (insulin-dependent diabetes mellitus, IDDM) is an autoimmune disease affecting about 0.12% of the world's population. Diabetic nephropathy (DN) is a major long-term complication of both types of diabetes and retains a high human, social and economic cost. Thus, the identification of markers for the early detection of DN represents a...
Conference Paper
Clinical data alignment plays a critical role in identifying important features for significant experiments. A central problem is data fusion i.e., how to correctly integrate data provided by different labs. This integration is done in order to increase ability of inferring target classes of controls and patients. Our paper proposes an approach bas...
Conference Paper
The application of various clustering techniques for large-scale gene-expression measurement experiments is an established method in bioinformatics. Clustering is also usually accompanied by functional characterization of gene sets by assessing statistical enrichments of structured vocabularies, such as the Gene Ontology (GO) [1]. If different clus...
Conference Paper
Full-text available
The biological interpretation of large-scale gene expression data is one of the challenges in current bioinformatics. The state-of-the- art approach is to perform clustering and then compute a functional characterization via enrichments by Gene Ontology terms (1). To better assist the interpretation of results, it may be useful to establish connec-...
Article
We deal with a complex game between Alice and Bob where each contender’s probability of victory grows monotonically by unknown amounts with the resources employed. For a fixed effort on Alice’s part, Bob increases his resources on the basis of the results for each round (victory, tie or defeat) with the aim of reducing the probability of defeat to...
Conference Paper
In this paper we apply a strategy to cluster gene expression data. In order to identify causal relationships among genes, we apply a pruning procedure [Chen et al., 1999] on the basis of the statistical cross-correlation function between couples of genes' time series. Finally we try to isolate genes' patterns in groups with positive causal relation...
Conference Paper
In this paper we describe the use of a correlation clustering algorithm [Chaitanya, 2004] to group expression level of genes in a microarray dataset. The clustering problem is formalized as a semi-defined optimization program, based on the correlation provided by two quantities, respectively related to an agreement and a disagreement between a pair...
Conference Paper
In this paper we describe a d face recognition system based on neural networks. The system consists of a modular architecture in which a set of probabilistic neural networks cooperate with the associated graphical models in recognising target people. The logic of this cooperation is quite simple: each network is able to discriminate between its “t...